Thread

I built non-autoregressive decision models with RL a year ago

1363 points · 319 comments · nandakishor_ml

dcow · 1789828104 · focus · HN ↗
I can understand why the author feels bitter but it still feels juvenile to me. Certainly both Jev and Laya are based on the research of countless prior papers and academics. Diogo decided to build a product out of the concept. The author didn't. Publishing research papers and model weights is probably part of the problem--it feels academic. If you look at the author's profile they focus on applying AI to healthcare. Not selling general AI type safety to AI pilled companies and devs. There's a big difference there. Whether that's good or bad you can argue all day. But for the author to expect otherwise is pretty weird. I do applaud them for not stewing too much on it and trying to do something about it, though.
1. operaopera · 1789828352 · focus · HN ↗
  I believe his qualms were with the "hype" in Jev's announcement: specifically calling this kind of model a breakthrough, without crediting previous art, and keeping everything closed source.
  1. prodigycorp · 1789828521 · focus · HN ↗
    And how is laya previous art? The project was vibecoded and posted yesterday.
    <a href="https://github.com/NandhaKishorM/laya/commits/main/" rel="nofollow">https://github.com/NandhaKishorM/laya/commits/main/
    <a href="https://huggingface.co/convaiinnovations/laya/commits/main" rel="nofollow">https://huggingface.co/convaiinnovations/laya/commits/main
    nandakishor_ml · 1789828748 · focus · HN ↗
    The paper is one year old. <a href="https://arxiv.org/abs/2510.01237" rel="nofollow">https://arxiv.org/abs/2510.01237 <a href="https://pypi.org/project/hallunox/" rel="nofollow">https://pypi.org/project/hallunox/
    prodigycorp · 1789829155 · focus · HN ↗
    Excuse me, but calibrating language models to accurately reflect probabilities did not start with you.
    nandakishor_ml · 1789829889 · focus · HN ↗
    I didn't claimed it bro it was first. Just shared the findings here.
    prodigycorp · 1789830550 · focus · HN ↗
    [dead]
    nandakishor_ml · 1789831288 · focus · HN ↗
    just not these jev guys not opensourcing their work
    verdverm · 1789834890 · focus · HN ↗
    You used a number of not open source projects in your paper, are you equally upset with them for this reason?
    dcow · 1789829787 · focus · HN ↗
    [dead]
    jeremyjh · 1789831861 · focus · HN ↗
    Generally they do credit the papers and/or people who developed the theory behind their product.
    charcircuit · 1789831957 · focus · HN ↗
    Researchers definitely do get paid for research. That Google company you mention funds research which can be integrated into their products.
    Matticus_Rex · 1789832828 · focus · HN ↗
    Sure, researchers get paid when they either do the research under contract or productize the research and sell it themselves. But they don't usually do the latter because that's quite difficult.
    verdverm · 1789834755 · focus · HN ↗
    Are you grouping academic research funded by grants under the contract category?
    To me, there is a meaningful difference and I'd add a third category, but I can also see the contract angle
    potterpie · 1789835360 · focus · HN ↗
    Ideas are cheap. But the ideas are cheap coming from anyone. The reason some ideas (like JEV's) are taking up our attention (as opposed to Laya's) is not because of their execution ability, but because venture funding now is subbing filling in for execution ability. I do understand your argument to this would be - "welcome to the world!" or "that's just how the world works" - but that does not mean we do not recognize the ideas that came well before "venture funding made it happen".
    I'd like to remind us all that there is a reason Joseph Liouville took the time to painstakingly review Galois’s chaotic manuscripts to credit him. It matters who did what before everyone else - if you do want to say "ideas are cheap" - we'd need to control for other variables before drawing conclusions.
    dcow · 1789928232 · focus · HN ↗
    I think we just have different definitions of execution. Getting VC funding and spending two years honing and SaaSifying an idea then dropping it with a hype train (yes paid for by VC funding) is certainly very different execution than someone writing a paper and publishing model weights on huggingface then vibe coding a “product” around it a year later the day after Jev is announced and the hype proves defensible and the idea is similar.
    prometheus1992 · 1789830960 · focus · HN ↗
    @prodigycorp - reading your comments here on this post - you seem pretty hurt by this post.
    prodigycorp · 1789831126 · focus · HN ↗
    Yeah, the reason why I am annoyed by it is because a person (who felt like a burner account of the laya creator) yesterday was haranguing me for saying that projects like this were vibe coded, posting the link to this project.
    I evaluated this project yesterday and found its claims un-credible. It's literally nothing like jev. That's some context behind why, a day later, I find it annoying that this is somehow the top story on HN.
    <a href="https://news.ycombinator.com/item?id=49752902">https://news.ycombinator.com/item?id=49752902
    prometheus1992 · 1789831430 · focus · HN ↗
    What is jev like? Did they release any research paper? I really think typesafe hired someone to boost their post because there was nothing "Breakthrough" about their product. At least this post has some touch with the reality that this functionality was available a year ago and was well known among ML people.
    prodigycorp · 1789831621 · focus · HN ↗
    I can't believe you say in another post that you have experience with bert and yet you don't understand the value of a generalist classifier.
    Good models take time and effort. There wasn't a good option for satisficers until a few days ago.
    jessrenoir · 1789912784 · focus · HN ↗
    It is standard discourse on here if you look backwards. Attention is All You Need sounds like a big nothingburger according to this post: <a href="https://news.ycombinator.com/item?id=15938082">https://news.ycombinator.com/item?id=15938082
    dcow · 1789834587 · focus · HN ↗
    > At least this post has some touch with the reality that this functionality was available a year ago and was well known among ML people.
    When you market a product you make exciting claims relative to the audience you’re engaging with. When was the last time you saw a product marketing page reverently lost all the academic research and prior art that came together to make a product possible?
    If Layla’s functionality was available in a SaaS form in a way that could be used by all the people who are excited about and using Jev, wouldn’t this research have won hearts and minds last year when it landed? I would have a lot more empathy for the author if they’d taken a product to market and nobody cared. But even then maybe the market wasn’t ready. There are still reasonable explanations why sometimes ideas take off. We’re on a venture capital forum this shouldn’t need an explanation.
    verdverm · 1789833061 · focus · HN ↗
    I agree with your analysis based on my own last night (on another HN post to this same gripe on reddit, before this blog post). OP received a lot of echo chamber support in the subreddit, and recommended to post to HN, so here we are.
    The work is very amateurish, the "paper" would be a strong reject if I were still peer reviewing.
    <a href="https://www.reddit.com/r/LocalLLaMA/comments/1wijo3e/i_literally_built_the_jev_architecture_one_year/" rel="nofollow">https://www.reddit.com/r/LocalLLaMA/comments/1wijo3e/i_liter...
    sreekanth850 · 1789834568 · focus · HN ↗
    I don't really see the breakthrough in Jev. Classification, scoring, routing and returning probabilities over predefined choices are all established problems. We implemented category routing in our own retrieval system in a slightly different way: embed the incoming query, compare it against category profiles and route to the highest cosine-similarity. Obviously Jev isn't similarity based, but the underlying task of making a constrained decision from predefined choices isn't novel. TypeSafe says Jev has a new architecture and RLCD training, but Jev's actual architecture, weights and training details aren't public. So we can't even claim Jev is specifically a BERT classifier, but also don't see enough public technical evidence yet to call the underlying idea a breakthrough. Atleast they should publish a technical paper to prove their idea is breakthrough.

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